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Targeting Impact versus Deprivation

Author

Listed:
  • Johannes Haushofer
  • Paul Niehaus
  • Carlos Paramo
  • Edward Miguel
  • Michael Walker

Abstract

A large literature has examined how best to target antipoverty programs to those most deprived in some sense (e.g., consumption). We examine the potential trade-off between this objective and targeting those most impacted by such programs. We work in the context of an NGO cash transfer program in Kenya, employing recent advances in machine learning methods and dynamic outcome data to learn proxy means tests that jointly target both objectives. Targeting solely on the basis of deprivation is not attractive in this setting under standard social welfare criteria unless the planner's preferences are extremely redistributive.

Suggested Citation

  • Johannes Haushofer & Paul Niehaus & Carlos Paramo & Edward Miguel & Michael Walker, 2025. "Targeting Impact versus Deprivation," American Economic Review, American Economic Association, vol. 115(6), pages 1936-1974, June.
    • Handle: RePEc:aea:aecrev:v:115:y:2025:i:6:p:1936-74
    DOI: 10.1257/aer.20221650
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    Citations

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    Cited by:

    1. Emily Breza & Arun G. Chandrasekhar & Davide Viviano, 2025. "Generalizability with ignorance in mind: learning what we do (not) know for archetypes discovery," Papers 2501.13355, arXiv.org, revised Jul 2025.
    2. repec:wbk:wbrwps:10251 is not listed on IDEAS
    3. Lena Morgon Banks & Shanquan Chen & Calum Davey & Kiza Eliza Islam & Elijah Kipchumba & Hannah Kuper & Munshi Sulaiman, 2025. "Disability-Inclusive Livelihoods and Household Economic Well-Being: Experimental Evidence from Northern Uganda," Trinity Economics Papers tep0625, Trinity College Dublin, Department of Economics.
    4. Jung, Woojin, 2023. "Mapping community development aid: Spatial analysis in Myanmar," World Development, Elsevier, vol. 164(C).
    5. Athey, Susan & Keleher, Niall & Spiess, Jann, 2025. "Machine learning who to nudge: Causal vs predictive targeting in a field experiment on student financial aid renewal," Journal of Econometrics, Elsevier, vol. 249(PC).
    6. Baird, Sarah & McIntosh, Craig & Özler, Berk & Pape, Utz, 2024. "Asset transfers and anti-poverty programs: Experimental evidence from Tanzania," Journal of Development Economics, Elsevier, vol. 166(C).
    7. Federico Crippa, 2024. "Regret Analysis in Threshold Policy Design," Papers 2404.11767, arXiv.org, revised Apr 2025.
    8. Bergstrom, Katy & Dodds, William, 2023. "Using schooling decisions to estimate the elasticity of marginal utility of consumption," Journal of Public Economics, Elsevier, vol. 224(C).
    9. Juan C. Yamin, 2025. "Poverty Targeting with Imperfect Information," Papers 2506.18188, arXiv.org.

    More about this item

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • L31 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - Nonprofit Institutions; NGOs; Social Entrepreneurship
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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